The Experts below are selected from a list of 21 Experts worldwide ranked by ideXlab platform
David Y. Feinstein - One of the best experts on this subject based on the ideXlab platform.
-
Modeling System Threat Probabilities Using Mixed-Radix Multiple-Valued Logic Decision Diagrams
2020Co-Authors: Theodore W. Manikas, Mitchell A. Thornton, David Y. FeinsteinAbstract:Design for security has become an area of increasing importance. This includes securing systems from both natural and intentional Threats. Extremely large and complex systems can have an accordingly large number of Threat scenarios, thus simply listing the Threats and devising countermeasures for each is ineffective and inefficient. The components of a large system may also have various states of failure, which cannot be captured by contemporary binary system models. To address this problem, we describe a Threat Cataloging methodology whereby a large number of Threats can be efficiently Cataloged and analyzed for common features. This allows countermeasures to be formulated that address a large number of Threats that share common features. The methodology utilizes Mixed-Radix Multiple-Valued Logic for describing the state of a large system and a multiple-valued decision diagram (MDD) for the Threat Catalog and analysis.
-
ISMVL - Modeling Medical System Threats with Conditional Probabilities Using Multiple-Valued Logic Decision Diagrams
2012 IEEE 42nd International Symposium on Multiple-Valued Logic, 2012Co-Authors: Theodore W. Manikas, David Y. Feinstein, Mitchell A. ThorntonAbstract:Design for medical system reliability has become an area of increasing importance. Medical system Threats, which include system failures as well as malicious attacks, often have interdependent events that can adversely affect system operation. To address these problems, we build upon our previous Threat Cataloging methodology such that a large number of interdependent Threats can be efficiently Cataloged and analyzed for common features. Our approach utilizes Multiple-Valued Logic for describing the state of a large system and a multiple-valued decision diagram (MDD) for the Threat Catalog and analysis.
-
Using Multiple-Valued Logic Decision Diagrams to Model System Threat Probabilities
2011 41st IEEE International Symposium on Multiple-Valued Logic, 2011Co-Authors: Theodore W. Manikas, Mitchell A. Thornton, David Y. FeinsteinAbstract:System security continues to be of increasing importance. To effectively address both natural and intentional Threats to large systems, the Threats must be Cataloged and analyzed. Extremely large and complex systems can have an accordingly large number of Threat scenarios. Simply listing the Threats and devising countermeasures for each is ineffective and not efficient. We describe a Threat Cataloging methodology whereby a large number of Threats can be efficiently Cataloged and analyzed for common features. This allows countermeasures to be formulated that address a large number of Threats that share common features. The methodology utilizes Multiple-Valued Logic for describing the state of a large system and a multiple-valued decision diagram (MDD) for the Threat Catalog and analysis.
-
ISMVL - Using Multiple-Valued Logic Decision Diagrams to Model System Threat Probabilities
2011 41st IEEE International Symposium on Multiple-Valued Logic, 2011Co-Authors: Theodore W. Manikas, Mitchell A. Thornton, David Y. FeinsteinAbstract:System security continues to be of increasing importance. To effectively address both natural and intentional Threats to large systems, the Threats must be Cataloged and analyzed. Extremely large and complex systems can have an accordingly large number of Threat scenarios. Simply listing the Threats and devising countermeasures for each is ineffective and not efficient. We describe a Threat Cataloging methodology whereby a large number of Threats can be efficiently Cataloged and analyzed for common features. This allows countermeasures to be formulated that address a large number of Threats that share common features. The methodology utilizes Multiple-Valued Logic for describing the state of a large system and a multiple-valued decision diagram (MDD) for the Threat Catalog and analysis.
Theodore W. Manikas - One of the best experts on this subject based on the ideXlab platform.
-
Modeling System Threat Probabilities Using Mixed-Radix Multiple-Valued Logic Decision Diagrams
2020Co-Authors: Theodore W. Manikas, Mitchell A. Thornton, David Y. FeinsteinAbstract:Design for security has become an area of increasing importance. This includes securing systems from both natural and intentional Threats. Extremely large and complex systems can have an accordingly large number of Threat scenarios, thus simply listing the Threats and devising countermeasures for each is ineffective and inefficient. The components of a large system may also have various states of failure, which cannot be captured by contemporary binary system models. To address this problem, we describe a Threat Cataloging methodology whereby a large number of Threats can be efficiently Cataloged and analyzed for common features. This allows countermeasures to be formulated that address a large number of Threats that share common features. The methodology utilizes Mixed-Radix Multiple-Valued Logic for describing the state of a large system and a multiple-valued decision diagram (MDD) for the Threat Catalog and analysis.
-
ISMVL - Modeling Medical System Threats with Conditional Probabilities Using Multiple-Valued Logic Decision Diagrams
2012 IEEE 42nd International Symposium on Multiple-Valued Logic, 2012Co-Authors: Theodore W. Manikas, David Y. Feinstein, Mitchell A. ThorntonAbstract:Design for medical system reliability has become an area of increasing importance. Medical system Threats, which include system failures as well as malicious attacks, often have interdependent events that can adversely affect system operation. To address these problems, we build upon our previous Threat Cataloging methodology such that a large number of interdependent Threats can be efficiently Cataloged and analyzed for common features. Our approach utilizes Multiple-Valued Logic for describing the state of a large system and a multiple-valued decision diagram (MDD) for the Threat Catalog and analysis.
-
Using Multiple-Valued Logic Decision Diagrams to Model System Threat Probabilities
2011 41st IEEE International Symposium on Multiple-Valued Logic, 2011Co-Authors: Theodore W. Manikas, Mitchell A. Thornton, David Y. FeinsteinAbstract:System security continues to be of increasing importance. To effectively address both natural and intentional Threats to large systems, the Threats must be Cataloged and analyzed. Extremely large and complex systems can have an accordingly large number of Threat scenarios. Simply listing the Threats and devising countermeasures for each is ineffective and not efficient. We describe a Threat Cataloging methodology whereby a large number of Threats can be efficiently Cataloged and analyzed for common features. This allows countermeasures to be formulated that address a large number of Threats that share common features. The methodology utilizes Multiple-Valued Logic for describing the state of a large system and a multiple-valued decision diagram (MDD) for the Threat Catalog and analysis.
-
ISMVL - Using Multiple-Valued Logic Decision Diagrams to Model System Threat Probabilities
2011 41st IEEE International Symposium on Multiple-Valued Logic, 2011Co-Authors: Theodore W. Manikas, Mitchell A. Thornton, David Y. FeinsteinAbstract:System security continues to be of increasing importance. To effectively address both natural and intentional Threats to large systems, the Threats must be Cataloged and analyzed. Extremely large and complex systems can have an accordingly large number of Threat scenarios. Simply listing the Threats and devising countermeasures for each is ineffective and not efficient. We describe a Threat Cataloging methodology whereby a large number of Threats can be efficiently Cataloged and analyzed for common features. This allows countermeasures to be formulated that address a large number of Threats that share common features. The methodology utilizes Multiple-Valued Logic for describing the state of a large system and a multiple-valued decision diagram (MDD) for the Threat Catalog and analysis.
Mitchell A. Thornton - One of the best experts on this subject based on the ideXlab platform.
-
Modeling System Threat Probabilities Using Mixed-Radix Multiple-Valued Logic Decision Diagrams
2020Co-Authors: Theodore W. Manikas, Mitchell A. Thornton, David Y. FeinsteinAbstract:Design for security has become an area of increasing importance. This includes securing systems from both natural and intentional Threats. Extremely large and complex systems can have an accordingly large number of Threat scenarios, thus simply listing the Threats and devising countermeasures for each is ineffective and inefficient. The components of a large system may also have various states of failure, which cannot be captured by contemporary binary system models. To address this problem, we describe a Threat Cataloging methodology whereby a large number of Threats can be efficiently Cataloged and analyzed for common features. This allows countermeasures to be formulated that address a large number of Threats that share common features. The methodology utilizes Mixed-Radix Multiple-Valued Logic for describing the state of a large system and a multiple-valued decision diagram (MDD) for the Threat Catalog and analysis.
-
ISMVL - Modeling Medical System Threats with Conditional Probabilities Using Multiple-Valued Logic Decision Diagrams
2012 IEEE 42nd International Symposium on Multiple-Valued Logic, 2012Co-Authors: Theodore W. Manikas, David Y. Feinstein, Mitchell A. ThorntonAbstract:Design for medical system reliability has become an area of increasing importance. Medical system Threats, which include system failures as well as malicious attacks, often have interdependent events that can adversely affect system operation. To address these problems, we build upon our previous Threat Cataloging methodology such that a large number of interdependent Threats can be efficiently Cataloged and analyzed for common features. Our approach utilizes Multiple-Valued Logic for describing the state of a large system and a multiple-valued decision diagram (MDD) for the Threat Catalog and analysis.
-
Using Multiple-Valued Logic Decision Diagrams to Model System Threat Probabilities
2011 41st IEEE International Symposium on Multiple-Valued Logic, 2011Co-Authors: Theodore W. Manikas, Mitchell A. Thornton, David Y. FeinsteinAbstract:System security continues to be of increasing importance. To effectively address both natural and intentional Threats to large systems, the Threats must be Cataloged and analyzed. Extremely large and complex systems can have an accordingly large number of Threat scenarios. Simply listing the Threats and devising countermeasures for each is ineffective and not efficient. We describe a Threat Cataloging methodology whereby a large number of Threats can be efficiently Cataloged and analyzed for common features. This allows countermeasures to be formulated that address a large number of Threats that share common features. The methodology utilizes Multiple-Valued Logic for describing the state of a large system and a multiple-valued decision diagram (MDD) for the Threat Catalog and analysis.
-
ISMVL - Using Multiple-Valued Logic Decision Diagrams to Model System Threat Probabilities
2011 41st IEEE International Symposium on Multiple-Valued Logic, 2011Co-Authors: Theodore W. Manikas, Mitchell A. Thornton, David Y. FeinsteinAbstract:System security continues to be of increasing importance. To effectively address both natural and intentional Threats to large systems, the Threats must be Cataloged and analyzed. Extremely large and complex systems can have an accordingly large number of Threat scenarios. Simply listing the Threats and devising countermeasures for each is ineffective and not efficient. We describe a Threat Cataloging methodology whereby a large number of Threats can be efficiently Cataloged and analyzed for common features. This allows countermeasures to be formulated that address a large number of Threats that share common features. The methodology utilizes Multiple-Valued Logic for describing the state of a large system and a multiple-valued decision diagram (MDD) for the Threat Catalog and analysis.
Mikael Gidlund - One of the best experts on this subject based on the ideXlab platform.
-
Security Risk Analysis of LoRaWAN and Future Directions
Future Internet, 2018Co-Authors: Ismail Butun, Nuno Pereira, Mikael GidlundAbstract:LoRa (along with its upper layers definition—LoRaWAN) is one of the most promising Low Power Wide Area Network (LPWAN) technologies for implementing Internet of Things (IoT)-based applications. Although being a popular technology, several works in the literature have revealed vulnerabilities and risks regarding the security of LoRaWAN v1.0 (the official 1st specification draft). The LoRa-Alliance has built upon these findings and introduced several improvements in the security and architecture of LoRa. The result of these efforts resulted in LoRaWAN v1.1, released on 11 October 2017. This work aims at reviewing and clarifying the security aspects of LoRaWAN v1.1. By following ETSI guidelines, we provide a comprehensive Security Risk Analysis of the protocol and discuss several remedies to the security risks described. A Threat Catalog is presented, along with discussions and analysis in view of the scale, impact, and likelihood of each Threat. To the best of the authors’ knowledge, this work is one of the first of its kind, by providing a detailed security risk analysis related to the latest version of LoRaWAN. Our analysis highlights important practical Threats, such as end-device physical capture, rogue gateway and self-replay, which require particular attention by developers and organizations implementing LoRa networks.
Ismail Butun - One of the best experts on this subject based on the ideXlab platform.
-
Security Risk Analysis of LoRaWAN and Future Directions
Future Internet, 2018Co-Authors: Ismail Butun, Nuno Pereira, Mikael GidlundAbstract:LoRa (along with its upper layers definition—LoRaWAN) is one of the most promising Low Power Wide Area Network (LPWAN) technologies for implementing Internet of Things (IoT)-based applications. Although being a popular technology, several works in the literature have revealed vulnerabilities and risks regarding the security of LoRaWAN v1.0 (the official 1st specification draft). The LoRa-Alliance has built upon these findings and introduced several improvements in the security and architecture of LoRa. The result of these efforts resulted in LoRaWAN v1.1, released on 11 October 2017. This work aims at reviewing and clarifying the security aspects of LoRaWAN v1.1. By following ETSI guidelines, we provide a comprehensive Security Risk Analysis of the protocol and discuss several remedies to the security risks described. A Threat Catalog is presented, along with discussions and analysis in view of the scale, impact, and likelihood of each Threat. To the best of the authors’ knowledge, this work is one of the first of its kind, by providing a detailed security risk analysis related to the latest version of LoRaWAN. Our analysis highlights important practical Threats, such as end-device physical capture, rogue gateway and self-replay, which require particular attention by developers and organizations implementing LoRa networks.